Signal transforms are widely used in signal processing to reveal
spectral properties of underlying signals. Many signal transforms are
data independent such as the Fourier transform, the discrete Cosine
transform (DCT), and the wavelet transform. However, there are
transforms that are data-driven. One famous example is KLT, which is
also known as the principal component analysis (PCA). KLT can
decorrelate the correlations among elements of an input signal vector
and generate a compact description. In the context of computer vision,
the eigenface for face recognition [1]} was
developed based on the 2D KLT.
